Link State Aware Dynamic Routing and Spectrum Allocation Strategy in Elastic Optical Networks
Compared with traditional wavelength division optical network, elastic optical network (EON) divides the network spectrum into smaller spectrum slots to improve the spectrum utilization, but the high-quality spectrum division also complicates the routing and spectrum allocation (RSA) problem. Variou...
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doaj-32763173766d4406a95a492c6e2086152021-03-30T03:10:14ZengIEEEIEEE Access2169-35362020-01-018450714508310.1109/ACCESS.2020.29776129020112Link State Aware Dynamic Routing and Spectrum Allocation Strategy in Elastic Optical NetworksYang Zhou0Qiang Sun1Siyu Lin2https://orcid.org/0000-0002-0492-2091School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing, ChinaSchool of Electronic and Information Engineering, Beijing Jiaotong University, Beijing, ChinaSchool of Electronic and Information Engineering, Beijing Jiaotong University, Beijing, ChinaCompared with traditional wavelength division optical network, elastic optical network (EON) divides the network spectrum into smaller spectrum slots to improve the spectrum utilization, but the high-quality spectrum division also complicates the routing and spectrum allocation (RSA) problem. Various strategies are proposed for reducing the RSA complexity and improving system traffic bearing capacity. However, previous RSA strategies do not consider the changing physical layer impairments that will also impact signal quality and even lead to violation of quality of transmission (QoT), the data cannot be transmitted correctly if the link state is degraded. Therefore, cross-layer optimization is desired, which means that different layer information is taken into account in the RSA strategy. In this paper, we propose a new link state-aware (LSA) RSA strategy to guarantee the QoT requirements under different link states. At first, the link state is evaluated based on chromatic dispersion (CD) and optical signal-to-noise ratio (OSNR), and a LightGBM model is exploited for CD and OSNR estimation. In LSA-RSA strategy, the link state is considered as a metric for qualified routing paths finding, and the link capacity is calculated based on the link state and used in spectrum allocation. Simulation results show that the average CD and OSNR estimation errors of the LightGBM model are 0.28ps/nm and 0.68dB, respectively. Under different link states and traffic loads, the LSA-RSA strategy can reduce traffic failure probability by more than 20%, and traffic load can increase 40Erlang when the bandwidth blocking probability equals 10%.https://ieeexplore.ieee.org/document/9020112/Cross-layer optimizationelastic optical networkmachine learningoptical performance monitoringrouting and spectrum allocation |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Yang Zhou Qiang Sun Siyu Lin |
spellingShingle |
Yang Zhou Qiang Sun Siyu Lin Link State Aware Dynamic Routing and Spectrum Allocation Strategy in Elastic Optical Networks IEEE Access Cross-layer optimization elastic optical network machine learning optical performance monitoring routing and spectrum allocation |
author_facet |
Yang Zhou Qiang Sun Siyu Lin |
author_sort |
Yang Zhou |
title |
Link State Aware Dynamic Routing and Spectrum Allocation Strategy in Elastic Optical Networks |
title_short |
Link State Aware Dynamic Routing and Spectrum Allocation Strategy in Elastic Optical Networks |
title_full |
Link State Aware Dynamic Routing and Spectrum Allocation Strategy in Elastic Optical Networks |
title_fullStr |
Link State Aware Dynamic Routing and Spectrum Allocation Strategy in Elastic Optical Networks |
title_full_unstemmed |
Link State Aware Dynamic Routing and Spectrum Allocation Strategy in Elastic Optical Networks |
title_sort |
link state aware dynamic routing and spectrum allocation strategy in elastic optical networks |
publisher |
IEEE |
series |
IEEE Access |
issn |
2169-3536 |
publishDate |
2020-01-01 |
description |
Compared with traditional wavelength division optical network, elastic optical network (EON) divides the network spectrum into smaller spectrum slots to improve the spectrum utilization, but the high-quality spectrum division also complicates the routing and spectrum allocation (RSA) problem. Various strategies are proposed for reducing the RSA complexity and improving system traffic bearing capacity. However, previous RSA strategies do not consider the changing physical layer impairments that will also impact signal quality and even lead to violation of quality of transmission (QoT), the data cannot be transmitted correctly if the link state is degraded. Therefore, cross-layer optimization is desired, which means that different layer information is taken into account in the RSA strategy. In this paper, we propose a new link state-aware (LSA) RSA strategy to guarantee the QoT requirements under different link states. At first, the link state is evaluated based on chromatic dispersion (CD) and optical signal-to-noise ratio (OSNR), and a LightGBM model is exploited for CD and OSNR estimation. In LSA-RSA strategy, the link state is considered as a metric for qualified routing paths finding, and the link capacity is calculated based on the link state and used in spectrum allocation. Simulation results show that the average CD and OSNR estimation errors of the LightGBM model are 0.28ps/nm and 0.68dB, respectively. Under different link states and traffic loads, the LSA-RSA strategy can reduce traffic failure probability by more than 20%, and traffic load can increase 40Erlang when the bandwidth blocking probability equals 10%. |
topic |
Cross-layer optimization elastic optical network machine learning optical performance monitoring routing and spectrum allocation |
url |
https://ieeexplore.ieee.org/document/9020112/ |
work_keys_str_mv |
AT yangzhou linkstateawaredynamicroutingandspectrumallocationstrategyinelasticopticalnetworks AT qiangsun linkstateawaredynamicroutingandspectrumallocationstrategyinelasticopticalnetworks AT siyulin linkstateawaredynamicroutingandspectrumallocationstrategyinelasticopticalnetworks |
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